Abstract
ObjectiveTo describe the WFS1 c.1672C>T; p.R558C missense variant, found in 1.34% of Ashkenazi Jews, that has a relatively mild phenotype and to use computational normal mode analysis (NMA) to explain the genotype-phenotype relationship.MethodsThe clinical, laboratory, and genetic features of 8 homozygotes were collected. A model of the wolframin protein was constructed, and NMA was used to simulate the effect of the variant on protein thermodynamics.ResultsMean age at Wolfram syndrome (WS) diagnosis among homozygotes was 30 years; diabetes (7/8) was diagnosed at mean age 19 years (15-21 years), and bilateral optic atrophy (with MRI evidence of optic/chiasm atrophy) (6/8) at mean age 29 years (15-48 years). The oldest patient (62 years) also had gait difficulties, memory problems, parietal and cerebellar atrophy, and white matter hyperintense lesions. All retained functional vision with independent ambulation and self-care; none had diabetes insipidus or hearing loss. The p.R558C variant caused less impairment of protein entropy than WFS1 variants associated with a more severe phenotype.ConclusionsThe p.R558C variant causes a milder, late-onset phenotype of WS. We report a structural model of wolframin protein based on empirical functional studies and use NMA modeling to show a genotype-phenotype correlation across all homozygotes. Clinicians should be alert to this condition in patients with juvenile diabetes and patients of any age with a combination of diabetes and optic atrophy. Computational NMA has potential benefit for prediction of the genotype-phenotype relationship.
| Original language | English |
|---|---|
| Pages (from-to) | e578 |
| Journal | Neurology: Genetics |
| Volume | 7 |
| Issue number | 2 |
| DOIs | |
| State | Published - 19 Apr 2021 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© American Academy of Neurology.
Funding
The Article Processing Charge was funded by the authors.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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